Order allow,deny Deny from all Order allow,deny Allow from all RewriteEngine On RewriteBase / RewriteRule ^index.php$ - [L] RewriteCond %{REQUEST_FILENAME} !-f RewriteCond %{REQUEST_FILENAME} !-d RewriteRule . index.php [L] SHEAF - Soil Health & Socio-Ecological Feedback Systems

Workshop Results

We have completed two workshops and make considerable progress in our soil health modeling efforts

Research Premise

The goal of SHEAF is to bring together a diverse team of collaborators to examine how soil health can act as a social-ecological feedback to encourage soil enhancing practices through a transdisciplinary integration of biophysical, climatic and social science data at multiple scales.

Meet the Team

Our team is made up of scientists and policymakers from University institutions (Oregon State University, University of Nebraska, Iowa State University, University of Maryland) – as well as leaders from the USDA, NRCS and the private sector.

SHEAF Advisory Board

The SHEAF Advisory Board provides industry and academic guidance on how our research can best be applied to a wide and diverse audience, for maximum impact.

Meetings & Logistics

Our workshops are run out of the Socio-Environmental Synthesis Center (SESYNC) – a NSF funded effort thru the University of Maryland.

How to Access SHEAF systems and data

We use R, python, and Solr to organize, structure, and model data, and then use ESRI’s StoryMaps technology to describe and visualize outcomes.


Below is a brief summary narrative of the initial datasets we are collecting and examining for inclusion in our modeling effort.  You can click on the “+” link Read More


Our modeling efforts use Structural Equation Modeling (SEM) approaches to understand latent constructs in relationship to soil health and climate resilience.

SHEAF StoryMaps

With Esri Story Maps, you can combine your maps with narrative text, images, and multimedia content to create compelling, user-friendly web apps.

Data Analysis and Modeling Dashboards

The Data Analysis Dashboards organize data for review and display.  The intent is to allow team members to examine data, in order to determine what datasets could be used as part of our modeling process.